Untitled

Pain dummy

Pain :: load dataset

mount_dir = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel';
con_list = dir(fullfile(mount_dir, '*/con_0022.nii'));
spm('Defaults','fMRI') 
con_fldr = {con_list.folder}; fname = {con_list.name};
con_files = strcat(con_fldr,'/', fname)';
con_data_obj = fmri_data(con_files);
Using default mask: /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/brainmask_canlab.nii
sampleto = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0022.nii'
loading mask. mapping volumes. 
checking that dimensions and voxel sizes of volumes are the same. 
Pre-allocating data array. Needed: 12379788 bytes
Loading image number:    31
Elapsed time is 62.342639 seconds.
Image names entered, but fullpath attribute is empty. Getting path info.
Number of unique values in dataset: 3041159  Bit rate: 21.54 bits
contrast_name = {'cue_P', 'cue_V', 'cue_C',...
    'cueXcue_P', 'cueXcue_V', 'cueXcue_C',...
    'stim_P', 'stim_V', 'stim_C',...
    'stimXcue_P', 'stimXcue_V', 'stimXcue_C',...
    'stimXint_P', 'stimXint_V', 'stimXint_C',...
    'motor', ...
    'simple_cue_P', 'simple_cue_V', 'simple_cue_C','simple_cue_G',...
    'simple_cueXcue_P', 'simple_cueXcue_V', 'simple_cueXcue_C','simple_cueXcue_G', ...
    'simple_stim_P', 'simple_stim_V', 'simple_stim_C','simple_stim_G',...
    'simple_stimXcue_P', 'simple_stimXcue_V', 'simple_stimXcue_C','simple_stimXcue_G',...
    'simple_stimXint_P', 'simple_stimXint_V','simple_stimXint_C', 'simple_stimXint_G'};

Pain :: check data coverage

m = mean(con_data_obj);
m.dat = sum(~isnan(con_data_obj.dat) & con_data_obj.dat ~= 0, 2);
orthviews(m, 'trans') % display
SPM12: spm_check_registration (v7759)              00:11:17 - 10/06/2022
========================================================================
Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1
Grouping contiguous voxels:   1 regions
ans = 1×1 cell array
    {1×1 region}

Pain :: Plot diagnostics, before l2norm

drawnow; snapnow

[wh_outlier_uncorr, wh_outlier_corr] = plot(con_data_obj)

______________________________________________________________ Outlier analysis ______________________________________________________________ global mean | global mean to var | spatial MAD | Missing values | 0 images Retained 3 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 22.58% Expected 1.55 outside 95% ellipsoid, found 3 Potential outliers based on mahalanobis distance: Bonferroni corrected: 3 images Cases 12 14 18 Uncorrected: 3 images Cases 12 14 18 Retained 6 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 48.39% Expected 1.55 outside 95% ellipsoid, found 1 Potential outliers based on mahalanobis distance: Bonferroni corrected: 0 images Cases Uncorrected: 1 images Cases 31 Mahalanobis (cov and corr, q<0.05 corrected): 3 images Outlier_count Percentage _____________ __________ global_mean 1 3.2258 global_mean_to_variance 0 0 missing_values 0 0 rmssd_dvars 0 0 spatial_variability 1 3.2258 mahal_cov_uncor 3 9.6774 mahal_cov_corrected 3 9.6774 mahal_corr_uncor 1 3.2258 mahal_corr_corrected 0 0 Overall_uncorrected 4 12.903 Overall_corrected 3 9.6774

SPM12: spm_check_registration (v7759) 00:11:41 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 (all) /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Grouping contiguous voxels: 1 regions

wh_outlier_uncorr = 31×1 logical array

wh_outlier_corr = 31×1 logical array

Pain :: run robfit

set(gcf,'Visible','on')
figure ('Visible', 'on');
drawnow, snapnow;

Pain :: remove outliers based on plot

con = con_data_obj;
disp(strcat("current length is ", num2str(size(con_data_obj.dat,2))))
current length is 31
%for s = 1:length(wh_outlier_corr)
    %disp(strcat("-------subject", num2str(s), "------"))
con.dat = con_data_obj.dat(:,~wh_outlier_corr);
con.image_names = con_data_obj.image_names(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×28 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [28×12 char]
              fullpath: [31×118 char]
           files_exist: [31×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0022.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.fullpath = con_data_obj.fullpath(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×28 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [28×12 char]
              fullpath: [28×118 char]
           files_exist: [31×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0022.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.files_exist = con_data_obj.files_exist(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×28 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [28×12 char]
              fullpath: [28×118 char]
           files_exist: [28×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0022.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
%end
disp(strcat("after removing ", num2str(sum(wh_outlier_corr)), " participants, size is now ",num2str(size(con.dat,2))))
after removing 3 participants, size is now 28

Pain :: plot diagnostics, after l2norm

imgs2 = con.rescale('l2norm_images');

Pain :: ttest

t = ttest(imgs2);

One-sample t-test Calculating t-statistics and p-values

orthviews(t)

SPM12: spm_check_registration (v7759) 00:11:49 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×1 struct}

drawnow, snapnow;

fdr_t = threshold(t, .05, 'fdr');

Image 1 FDR q < 0.050 threshold is 0.000000 Image 1 0 contig. clusters, sizes to Positive effect: 0 voxels, min p-value: 0.00000226 Negative effect: 0 voxels, min p-value: 0.00000429

orthviews(fdr_t)

SPM12: spm_check_registration (v7759) 00:11:50 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×1 struct}

drawnow, snapnow;

create_figure('montage'); axis off

montage(fdr_t)

Setting up fmridisplay objects

ans =

fmridisplay with properties: overlay: '/Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img' SPACE: [1×1 struct] activation_maps: {} montage: {[1×1 struct] [1×1 struct] [1×1 struct] [1×1 struct] [1×1 struct]} surface: {} orthviews: {} history: {} history_descrip: [] additional_info: ''

drawnow, snapnow;

Vicarious dummy

clear all

Vicarious :: load dataset

mount_dir = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel';
con_list = dir(fullfile(mount_dir, '*/con_0023.nii'));
spm('Defaults','fMRI') 
con_fldr = {con_list.folder}; fname = {con_list.name};
con_files = strcat(con_fldr,'/', fname)';
con_data_obj = fmri_data(con_files);
Using default mask: /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/brainmask_canlab.nii
Direct calls to spm_defauts are deprecated.
Please use spm('Defaults',modality) or spm_get_defaults instead.
sampleto = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0023.nii'
loading mask. mapping volumes. 
checking that dimensions and voxel sizes of volumes are the same. 
Pre-allocating data array. Needed: 12379788 bytes
Loading image number:    31
Elapsed time is 76.562868 seconds.
Image names entered, but fullpath attribute is empty. Getting path info.
Number of unique values in dataset: 3040108  Bit rate: 21.54 bits
contrast_name = {'cue_P', 'cue_V', 'cue_C',...
    'cueXcue_P', 'cueXcue_V', 'cueXcue_C',...
    'stim_P', 'stim_V', 'stim_C',...
    'stimXcue_P', 'stimXcue_V', 'stimXcue_C',...
    'stimXint_P', 'stimXint_V', 'stimXint_C',...
    'motor', ...
    'simple_cue_P', 'simple_cue_V', 'simple_cue_C','simple_cue_G',...
    'simple_cueXcue_P', 'simple_cueXcue_V', 'simple_cueXcue_C','simple_cueXcue_G', ...
    'simple_stim_P', 'simple_stim_V', 'simple_stim_C','simple_stim_G',...
    'simple_stimXcue_P', 'simple_stimXcue_V', 'simple_stimXcue_C','simple_stimXcue_G',...
    'simple_stimXint_P', 'simple_stimXint_V','simple_stimXint_C', 'simple_stimXint_G'};

Vicarious :: check data coverage

m = mean(con_data_obj);

m.dat = sum(~isnan(con_data_obj.dat) & con_data_obj.dat ~= 0, 2);

orthviews(m, 'trans') % display

SPM12: spm_check_registration (v7759) 00:13:40 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Grouping contiguous voxels: 1 regions

ans = 1×1 cell array

{1×1 region}

Vicarious :: Plot diagnostics, before l2norm

drawnow; snapnow

[wh_outlier_uncorr, wh_outlier_corr] = plot(con_data_obj)

______________________________________________________________ Outlier analysis ______________________________________________________________ global mean | global mean to var | spatial MAD | Missing values | 0 images Retained 4 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 29.03% Expected 1.55 outside 95% ellipsoid, found 4 Potential outliers based on mahalanobis distance: Bonferroni corrected: 2 images Cases 5 8 Uncorrected: 4 images Cases 5 7 8 21 Retained 8 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 61.29% Expected 1.55 outside 95% ellipsoid, found 0 Potential outliers based on mahalanobis distance: Bonferroni corrected: 0 images Cases Uncorrected: 0 images Cases Mahalanobis (cov and corr, q<0.05 corrected): 2 images Outlier_count Percentage _____________ __________ global_mean 1 3.2258 global_mean_to_variance 0 0 missing_values 0 0 rmssd_dvars 0 0 spatial_variability 0 0 mahal_cov_uncor 4 12.903 mahal_cov_corrected 2 6.4516 mahal_corr_uncor 0 0 mahal_corr_corrected 0 0 Overall_uncorrected 4 12.903 Overall_corrected 2 6.4516

SPM12: spm_check_registration (v7759) 00:14:09 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 (all) /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Grouping contiguous voxels: 1 regions

wh_outlier_uncorr = 31×1 logical array

wh_outlier_corr = 31×1 logical array

Vicarious :: run robfit

set(gcf,'Visible','on')
figure ('Visible', 'on');
drawnow, snapnow;

Vicarious :: remove outliers based on plot

con = con_data_obj;
disp(strcat("current length is ", num2str(size(con_data_obj.dat,2))))
current length is 31
%for s = 1:length(wh_outlier_corr)
  %  disp(strcat("-------subject", num2str(s), "------"))
con.dat = con_data_obj.dat(:,~wh_outlier_corr);
con.image_names = con_data_obj.image_names(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×29 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [29×12 char]
              fullpath: [31×118 char]
           files_exist: [31×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0023.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.fullpath = con_data_obj.fullpath(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×29 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [29×12 char]
              fullpath: [29×118 char]
           files_exist: [31×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0023.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.files_exist = con_data_obj.files_exist(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×29 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [29×12 char]
              fullpath: [29×118 char]
           files_exist: [29×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0023.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
%end
disp(strcat("after removing ", num2str(sum(wh_outlier_corr)), " participants, size is now ",num2str(size(con.dat,2))))
after removing 2 participants, size is now 29

Vicarious :: plot diagnostics, after l2norm

imgs2 = con.rescale('l2norm_images');

Vicarious :: ttest

t = ttest(imgs2);

One-sample t-test Calculating t-statistics and p-values

orthviews(t)

SPM12: spm_check_registration (v7759) 00:14:16 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×1 struct}

drawnow, snapnow;

fdr_t = threshold(t, .05, 'fdr');

Image 1 FDR q < 0.050 threshold is 0.000169 Image 1 11 contig. clusters, sizes 1 to 159 Positive effect: 1 voxels, min p-value: 0.00009525 Negative effect: 337 voxels, min p-value: 0.00000000

orthviews(fdr_t)

SPM12: spm_check_registration (v7759) 00:14:18 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×11 struct}

drawnow, snapnow;

create_figure('montage'); axis off

montage(fdr_t)

Setting up fmridisplay objects

sagittal montage: 1 voxels displayed, 337 not displayed on these slices

sagittal montage: 0 voxels displayed, 338 not displayed on these slices sagittal montage: 0 voxels displayed, 338 not displayed on these slices axial montage: 79 voxels displayed, 259 not displayed on these slices

axial montage: 67 voxels displayed, 271 not displayed on these slices

ans =

fmridisplay with properties: overlay: '/Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img' SPACE: [1×1 struct] activation_maps: {[1×1 struct]} montage: {[1×1 struct] [1×1 struct] [1×1 struct] [1×1 struct] [1×1 struct]} surface: {} orthviews: {} history: {} history_descrip: [] additional_info: ''

drawnow, snapnow;

Cognitive dummy

Cognitive :: load dataset

mount_dir = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel';
con_list = dir(fullfile(mount_dir, '*/con_0024.nii'));
spm('Defaults','fMRI') 
con_fldr = {con_list.folder}; fname = {con_list.name};
con_files = strcat(con_fldr,'/', fname)';
con_data_obj = fmri_data(con_files);
Using default mask: /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/brainmask_canlab.nii
sampleto = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0024.nii'
loading mask. mapping volumes. 
checking that dimensions and voxel sizes of volumes are the same. 
Pre-allocating data array. Needed: 12379788 bytes
Loading image number:    31
Elapsed time is 61.889130 seconds.
Image names entered, but fullpath attribute is empty. Getting path info.
Number of unique values in dataset: 3039764  Bit rate: 21.54 bits
contrast_name = {'cue_P', 'cue_V', 'cue_C',...
    'cueXcue_P', 'cueXcue_V', 'cueXcue_C',...
    'stim_P', 'stim_V', 'stim_C',...
    'stimXcue_P', 'stimXcue_V', 'stimXcue_C',...
    'stimXint_P', 'stimXint_V', 'stimXint_C',...
    'motor', ...
    'simple_cue_P', 'simple_cue_V', 'simple_cue_C','simple_cue_G',...
    'simple_cueXcue_P', 'simple_cueXcue_V', 'simple_cueXcue_C','simple_cueXcue_G', ...
    'simple_stim_P', 'simple_stim_V', 'simple_stim_C','simple_stim_G',...
    'simple_stimXcue_P', 'simple_stimXcue_V', 'simple_stimXcue_C','simple_stimXcue_G',...
    'simple_stimXint_P', 'simple_stimXint_V','simple_stimXint_C', 'simple_stimXint_G'};

Cognitive :: check data coverage

m = mean(con_data_obj);

m.dat = sum(~isnan(con_data_obj.dat) & con_data_obj.dat ~= 0, 2);

orthviews(m, 'trans') % display

SPM12: spm_check_registration (v7759) 00:15:56 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Grouping contiguous voxels: 1 regions

ans = 1×1 cell array

{1×1 region}

Cognitive :: Plot diagnostics, before l2norm

drawnow; snapnow

[wh_outlier_uncorr, wh_outlier_corr] = plot(con_data_obj)

______________________________________________________________ Outlier analysis ______________________________________________________________ global mean | global mean to var | spatial MAD | Missing values | 0 images Retained 5 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 38.71% Expected 1.55 outside 95% ellipsoid, found 4 Potential outliers based on mahalanobis distance: Bonferroni corrected: 2 images Cases 7 27 Uncorrected: 4 images Cases 2 7 18 27 Retained 9 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 58.06% Expected 1.55 outside 95% ellipsoid, found 0 Potential outliers based on mahalanobis distance: Bonferroni corrected: 0 images Cases Uncorrected: 0 images Cases Mahalanobis (cov and corr, q<0.05 corrected): 2 images Outlier_count Percentage _____________ __________ global_mean 1 3.2258 global_mean_to_variance 0 0 missing_values 0 0 rmssd_dvars 0 0 spatial_variability 1 3.2258 mahal_cov_uncor 4 12.903 mahal_cov_corrected 2 6.4516 mahal_corr_uncor 0 0 mahal_corr_corrected 0 0 Overall_uncorrected 4 12.903 Overall_corrected 2 6.4516

SPM12: spm_check_registration (v7759) 00:16:18 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 (all) /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Grouping contiguous voxels: 1 regions

wh_outlier_uncorr = 31×1 logical array

wh_outlier_corr = 31×1 logical array

Cognitive :: run robfit

set(gcf,'Visible','on')
figure ('Visible', 'on');
drawnow, snapnow;

Cognitive :: remove outliers based on plot

con = con_data_obj;
disp(strcat("current length is ", num2str(size(con_data_obj.dat,2))))
current length is 31
%for s = 1:length(wh_outlier_corr)
   % disp(strcat("-------subject", num2str(s), "------"))
con.dat = con_data_obj.dat(:,~wh_outlier_corr);
con.image_names = con_data_obj.image_names(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×29 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [29×12 char]
              fullpath: [31×118 char]
           files_exist: [31×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0024.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.fullpath = con_data_obj.fullpath(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×29 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [29×12 char]
              fullpath: [29×118 char]
           files_exist: [31×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0024.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.files_exist = con_data_obj.files_exist(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×29 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [29×12 char]
              fullpath: [29×118 char]
           files_exist: [29×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0024.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
%end
disp(strcat("after removing ", num2str(sum(wh_outlier_corr)), " participants, size is now ",num2str(size(con.dat,2))))
after removing 2 participants, size is now 29

Cognitive:: plot diagnostics, after l2norm

imgs2 = con.rescale('l2norm_images');

Cognitive :: ttest

t = ttest(imgs2);

One-sample t-test Calculating t-statistics and p-values

orthviews(t)

SPM12: spm_check_registration (v7759) 00:16:23 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×1 struct}

drawnow, snapnow;

fdr_t = threshold(t, .05, 'fdr');

Image 1 FDR q < 0.050 threshold is 0.000000 Image 1 0 contig. clusters, sizes to Positive effect: 0 voxels, min p-value: 0.00009441 Negative effect: 0 voxels, min p-value: 0.00002944

orthviews(fdr_t)

SPM12: spm_check_registration (v7759) 00:16:25 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×1 struct}

drawnow, snapnow;

create_figure('montage'); axis off

montage(fdr_t)

Setting up fmridisplay objects

ans =

drawnow, snapnow;

General dummy

General :: load dataset

mount_dir = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel';
con_list = dir(fullfile(mount_dir, '*/con_0025.nii'));
spm('Defaults','fMRI') 
con_fldr = {con_list.folder}; fname = {con_list.name};
con_files = strcat(con_fldr,'/', fname)';
con_data_obj = fmri_data(con_files);
Using default mask: /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/brainmask_canlab.nii
sampleto = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0025.nii'
loading mask. mapping volumes. 
checking that dimensions and voxel sizes of volumes are the same. 
Pre-allocating data array. Needed: 12379788 bytes
Loading image number:    31
Elapsed time is 65.904355 seconds.
Image names entered, but fullpath attribute is empty. Getting path info.
Number of unique values in dataset: 3042449  Bit rate: 21.54 bits
contrast_name = {'cue_P', 'cue_V', 'cue_C',...
    'cueXcue_P', 'cueXcue_V', 'cueXcue_C',...
    'stim_P', 'stim_V', 'stim_C',...
    'stimXcue_P', 'stimXcue_V', 'stimXcue_C',...
    'stimXint_P', 'stimXint_V', 'stimXint_C',...
    'motor', ...
    'simple_cue_P', 'simple_cue_V', 'simple_cue_C','simple_cue_G',...
    'simple_cueXcue_P', 'simple_cueXcue_V', 'simple_cueXcue_C','simple_cueXcue_G', ...
    'simple_stim_P', 'simple_stim_V', 'simple_stim_C','simple_stim_G',...
    'simple_stimXcue_P', 'simple_stimXcue_V', 'simple_stimXcue_C','simple_stimXcue_G',...
    'simple_stimXint_P', 'simple_stimXint_V','simple_stimXint_C', 'simple_stimXint_G'};

General :: check data coverage

m = mean(con_data_obj);

m.dat = sum(~isnan(con_data_obj.dat) & con_data_obj.dat ~= 0, 2);

orthviews(m, 'trans') % display

SPM12: spm_check_registration (v7759) 00:18:04 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Grouping contiguous voxels: 1 regions

ans = 1×1 cell array

{1×1 region}

General :: Plot diagnostics, before l2norm

drawnow; snapnow

[wh_outlier_uncorr, wh_outlier_corr] = plot(con_data_obj)

______________________________________________________________ Outlier analysis ______________________________________________________________ global mean | global mean to var | spatial MAD | Missing values | 0 images Retained 2 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 29.03% Expected 1.55 outside 95% ellipsoid, found 3 Potential outliers based on mahalanobis distance: Bonferroni corrected: 1 images Cases 18 Uncorrected: 3 images Cases 6 12 18 Retained 9 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 45.16% Expected 1.55 outside 95% ellipsoid, found 0 Potential outliers based on mahalanobis distance: Bonferroni corrected: 0 images Cases Uncorrected: 0 images Cases Mahalanobis (cov and corr, q<0.05 corrected): 1 images Outlier_count Percentage _____________ __________ global_mean 2 6.4516 global_mean_to_variance 0 0 missing_values 0 0 rmssd_dvars 0 0 spatial_variability 0 0 mahal_cov_uncor 3 9.6774 mahal_cov_corrected 1 3.2258 mahal_corr_uncor 0 0 mahal_corr_corrected 0 0 Overall_uncorrected 3 9.6774 Overall_corrected 1 3.2258

SPM12: spm_check_registration (v7759) 00:18:25 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 (all) /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Grouping contiguous voxels: 1 regions

wh_outlier_uncorr = 31×1 logical array

wh_outlier_corr = 31×1 logical array

General :: run robfit

set(gcf,'Visible','on')
figure ('Visible', 'on');
drawnow, snapnow;

General :: remove outliers based on plot

con = con_data_obj;
disp(strcat("current length is ", num2str(size(con_data_obj.dat,2))))
current length is 31
%for s = 1:length(wh_outlier_corr)
   % disp(strcat("-------subject", num2str(s), "------"))
con.dat = con_data_obj.dat(:,~wh_outlier_corr);
con.image_names = con_data_obj.image_names(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×30 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [30×12 char]
              fullpath: [31×118 char]
           files_exist: [31×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0025.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.fullpath = con_data_obj.fullpath(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×30 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [30×12 char]
              fullpath: [30×118 char]
           files_exist: [31×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0025.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.files_exist = con_data_obj.files_exist(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×30 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [30×12 char]
              fullpath: [30×118 char]
           files_exist: [30×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-03_CEScsA_24dofcsd/1stLevel/sub-0008/con_0025.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
%end
disp(strcat("after removing ", num2str(sum(wh_outlier_corr)), " participants, size is now ",num2str(size(con.dat,2))))
after removing 1 participants, size is now 30

General:: plot diagnostics, after l2norm

imgs2 = con.rescale('l2norm_images');

General :: ttest

t = ttest(imgs2);

One-sample t-test Calculating t-statistics and p-values

orthviews(t)

SPM12: spm_check_registration (v7759) 00:18:32 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×1 struct}

drawnow, snapnow;

fdr_t = threshold(t, .05, 'fdr');

Image 1 FDR q < 0.050 threshold is 0.000542 Image 1 58 contig. clusters, sizes 1 to 291 Positive effect: 3 voxels, min p-value: 0.00012875 Negative effect: 1078 voxels, min p-value: 0.00000000

orthviews(fdr_t)

SPM12: spm_check_registration (v7759) 00:18:34 - 10/06/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×58 struct}

drawnow, snapnow;

create_figure('montage'); axis off

montage(fdr_t)

Setting up fmridisplay objects

sagittal montage: 3 voxels displayed, 1078 not displayed on these slices

sagittal montage: 0 voxels displayed, 1081 not displayed on these slices axial montage: 209 voxels displayed, 872 not displayed on these slices

axial montage: 189 voxels displayed, 892 not displayed on these slices

ans =

fmridisplay with properties: overlay: '/Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img' SPACE: [1×1 struct] activation_maps: {[1×1 struct]} montage: {[1×1 struct] [1×1 struct] [1×1 struct] [1×1 struct] [1×1 struct]} surface: {} orthviews: {} history: {} history_descrip: [] additional_info: ''

drawnow, snapnow;